Data Scientist

Role & responsibilities

• Design, build, and optimize machine/deep learning models, including predictive models, recommendation systems, and Gen-AI-based solutions.
• Develop and implement advanced AI agents capable of performing autonomous tasks, decision-making, and executing requirement-specific workflows.
• Prompt engineer to develop new and enhance existing Gen-AI applications. (Chatbots, RAG)
• Perform advanced data manipulation, cleansing, and analysis to extract actionable insights from structured and unstructured data.
• Create scalable and efficient recommendation systems that enhance user personalization and engagement.
• Design and deploy AI-driven chatbots and virtual assistants, focusing on natural language understanding and contextual relevance.
• Implement and optimize machine and deep learning models for NLP tasks, including text classification, sentiment analysis, and language generation.
• Explore, develop, and deploy state-of-the-art technologies for AI agents, integrating them with broader enterprise systems.
• Collaborate with cross-functional teams to gather business requirements and deliver AI-driven solutions tailored to specific use cases.
• Automate workflows using advanced AI tools and frameworks to increase efficiency and reduce manual interventions.
• Stay informed about cutting-edge advancements in AI, machine learning, NLP, and GenAI applications, and assess their relevance to the organization.
• Effectively communicate technical solutions and findings to both technical and non-technical stakeholders.

Required:

• At least 3 years of experience working with data sciences.
• Python proficiency and hands-on experience with libraries like (Pandas, Numpy, Matplotlib, NLTK, Sklearn, and Tensorflow)
• Proven experience in designing and implementing AI agents and autonomous systems.
• Strong expertise in machine learning, including predictive modeling and recommendation systems.
• Hands-on experience with deep learning frameworks like TensorFlow or PyTorch, focusing on NLP and AI-driven solutions.
• Advanced understanding of natural language processing (NLP) techniques and tools, including transformers like BERT, GPT, or similar models including open-source LLMs.
• Experience in prompt engineering for AI models to enhance functionality and adaptability.
• Strong knowledge of cloud platforms (AWS) for deploying and scaling AI models.
• Familiarity with AI agent frameworks like LangChain, OpenAI APIs, or other agent-building tools.
• Advanced skills in Relational databases [Postgres], Vector Database, querying, analytics, semantic search, and data manipulation.
• Strong problem-solving and critical-thinking skills, with the ability to handle complex technical challenges.
• Hands-on experience working with API frameworks like Flask, FastAPI, etc. Git and GitHub proficiency.
• Excellent communication & documentation skills to articulate complex ideas to diverse audiences.

Preferred:

• Hands-on experience building and deploying conversational AI, chatbots, and virtual assistants.
• Familiarity with MLOps pipelines and CI/CD for AI/ML workflows.
• Experience with reinforcement learning or multi-agent systems.
• BE (OR Master) in Computer Science, Data Science, or Artificial Intelligence.
• Agentic AI systems using frameworks like Langchain or similar.